A Study of the Relationships Between Level of Pain, Analgesic Requirements, and Quality of Life Associated with Total Knee Arthroplasty
Bibliographic record
Abstract
Patients suffering from various arthritic conditions such as osteoarthritis (OA) seek relief through total knee arthroplasty (TKA). The surgery itself has been proven successful; however it carries a difficult and challenging recovery period. The purpose of this study was to examine the relationships between pain levels and quality of life (QOL), and to determine the effect pain has on QOL measures pre- and post TKA. A sample of thirteen participants receiving care at a local orthopedic clinic was selected from the North Florida area via convenience sampling. Participants were asked to complete a demographic questionnaire, the Western Ontario and McMaster Universities (WOMAC) Arthritis Index, and a medication journal preoperatively, and again at six-weeks postoperatively. The WOMAC has been thoroughly tested for reliability and validity across multiple research studies. Inclusion criteria were limited to those having TKA secondary only to OA, and those subsequently entering a rehabilitation program after hospital discharge. The patients had to be able to read and understand English, and be able to communicate their pain levels through a mediation journal and the WOMAC. The hypotheses concerned the presence of a relationship between pain and QOL measures pre- and postoperatively. Paired samples t-test and Pearson's Correlational analyses were used to examine potential relationships. As a result of the collected data, there were significant relationships between preoperative pain levels and WOMAC scores (r = .814, p = .001), preoperative and postoperative pain levels (t = 4.177, p = .001), postoperative pain levels and WOMAC scores (r = .903, p = .000), and preoperative and postoperative WOMAC scores (t = 5.378, p = .000). Medication journaling did not provide sufficient data to infer to the general orthopedic population. Overall, decreases in postoperative pain levels correlated with decreases in total WOMAC scores, signifying improvements in pain and QOL. Based on these results, it is the responsibility of the advanced practice nurse to accurately assess pain and its impact on QOL in this population of OA sufferers. The integration of the WOMAC in pain assessment may help assist in tailoring effective pain management regimens during the course of TKA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".